Defamilization typology revisited: Is the state or the market the driving force behind childcare defamilization?

Abstract

This study employs fuzzy set analysis to categorize childcare policies across 19 OECD member countries, emphasizing defamilization strategies focusing on policy tool mixes. It investigates whether these strategies are state-centered or market-centered by analyzing the directness of funding, service creation, and the coerciveness of quality regulations. Key variables include the co-payment proportion of dual-income families, public preschool utilization rates, and monitoring intensity of childcare services, with women’s employment rates as the outcome. The analysis identifies six childcare service models based on government involvement and market dynamics, revealing that women’s employment rates tend to be higher when childcare services are predominantly market-driven. This suggests that market forces play a significant role in the defamilization of childcare, particularly as women’s participation in the labor market grows.

Keywords

Childcare policy defamilization policy tools typology women’s employment

Introduction

Welfare state typology and the concept of defamilization have expanded the horizon of social policy discipline. The concept of defamilization derives from feminist scholars’ criticism that decommodification for welfare state typology, as presented by Esping-Andersen (1990), fails to capture gender perspectives. Defamilization is defined by socialization of the burden of family support, allowing family members to maintain an appropriate standard of living regardless of their family relationships or roles (Esping-Andersen, 1999; Lietner, 2003; Lister, 1994). In other words, care work such as child and elderly care, which is traditionally performed by family members – primarily women – is socialized.

The discussion of welfare state typology from a gender perspective, encompassing the concept of defamilization, is ongoing and has focused on how individual welfare states reflect women’s right to work and parental rights when implementing family-related social policies. Most studies have examined the defamilistic characteristics of individual states by focusing on policies that appear to alleviate the gender gap in the labor market, such as parental leave and childcare policies (Bambra, 2007; Cho, 2014; Gough, 2001).

However, although budget size, provision, and utilization of related policies all seem to have positive effects on defamilization, these aspects cannot fully reveal whether defamilization is occurring at the household level. Research must examine whether defamilization is driven by the state or the market, and whether that leads to disparities in policy outcomes. Identifying the main agent of defamilization could provide individual states with a theoretical background for regulating policy tool mixes when defining the characteristics of defamilization and replacing care work with various social services. In addition, market-centric defamilization strategies could result in differences in care service quality based on the combination of state support and voluntary influx of additional funds from families. In other words, individual families’ choices could cause disparity, even inequality, in the provision of social rights. If families address childcare deficits by purchasing services of varying quality and cost, disparities in care and early education quality may emerge based on their economic resources. State intervention to reduce these gaps during the defamilization of childcare is crucial for promoting social equity and mitigating the effects of socio-demographic backgrounds on children’s development.

This study employs fuzzy set analysis to examine the defamilization of childcare services across individual OECD countries. It adopts and extends criteria for defamilization proposed by prominent feminist scholars such as Bambra (2007) and Cho (2014). The typology developed in this research evaluates the extent of state involvement in financing, providing, and regulating childcare services, using metrics such as the financial burden on households, public facility utilization rates, and systematic monitoring of childcare services. This approach is grounded in Kwon’s (2009) framework of policy tool mixes. The study posits that the specific policy tools used to enhance access to childcare services may result in disparities among families in terms of actual defamilization. By analyzing the interplay between the state and the market, the study aims to generate policy insights for promoting more effective defamilization of care.

Background

Defamilization

Understanding the concept of defamilization requires a prerequisite understanding of decommodification – the principle that individuals, regardless of economic participation, should be able to maintain an appropriate standard of living and that welfare states are responsible for decommodifying individuals or families (Esping-Andersen, 1990). The concept of decommodification has been criticized for its presumption that all individuals are commodified; in fact, the presumption applies only to full-time male workers (Orloff, 1993). Thus, decommodification explains the relationship between a welfare state and the average male worker only and does not apply to non-commodified or partially commodified individuals, especially women. Accordingly, welfare state typologies have faced criticism for failing to account for women’s commodified status and for placing a dual burden on them by combining employment with family care responsibilities (Esping-Andersen, 1999).

Lister (1994) argues that to accurately measure economic independence, decommodification (i.e. individuals’ ability to maintain an appropriate standard of living regardless of their participation in the labor market) must be supplemented by the concept of defamilization. This concept is defined as individuals’ ability to maintain an appropriate standard of living through either paid labor or social security, regardless of their family relationships (such as marital status) or their roles in unpaid care work within the family (Lister, 1994). In other words, if individuals’ standard of living changes depending on marital status (e.g. being single, divorced, or widowed), if they cannot perform reasonably paid work due to care burdens, or if social security amounts differ depending on marital status, defamilization is low.

Esping-Andersen (1999) conceptualized defamilization as a method to reduce the care burden on families and the welfare dependency of individuals, but did not thoroughly consider in-family gender relations, as compared to Lister (1994). Esping-Andersen (1999) argued that defamilization was not an anti-family concept, such as dismantling of families, but the alleviation of care burdens on families through market- or state-provided social services. In contrast, Lister (1994) defined defamilization as state-driven changes in the power balance and relationship between care providers and receivers, and in the conditions of care relations, through changes to wages or the conditions of receiving wages.

Whereas Lister’s (1994) conception of defamilization focuses on status and role inequality within the family, and prioritizes changing that status or role through state-provided wages and services or changes to the conditions of receiving wages, Esping-Andersen’s conception suggests that the care burden could also be alleviated by market-provided services and wages. Defamilization driven by the welfare state may be more desirable, because even if service costs remain low, market-driven defamilization would still be relatively expensive and consequently inaccessible to people in low income brackets (Esping-Andersen, 1999).

Welfare state typology considering defamilization

Esping-Andersen (1999) specifies four indicators for defamilization in welfare states: expenditure for services, cash benefits for families with children, supply of public childcare facilities, and supply of elderly care services. Specifically, these indicators are measured by the percentage of GDP spent on non-medical family-related services, family allowances, and tax deductions; childcare facilities for infants under the age of three; and the percentage of elderly citizens over the age of 65 receiving care services. However, identifying defamilization based only on state-provided benefits and services to families is limited because it does not consider individuals’ roles and relationships within the family, an important aspect of the concept. Thus, Esping-Andersen’s indicators classify defamilization based on the existence and management of related policies and budget allocations, regardless of the actual impacts of these policies on defamilization in individual households.

To ensure accessibility to paid work, the state must provide the support that allows family members burdened with care work to function simultaneously in the labor market. Esping-Andersen’s (1999) suggested indicators do not sufficiently reflect systems other than childcare facilities that alleviate incompatibility between work and family responsibilities, such as parental or maternity leave. In addition, because the indicators assess factors such as percentage of GDP spent on services and service recipient ratios, they cannot capture whether family members burdened with care work actually benefit from these systems. To determine this, the method in which benefits and services are provided must be measured in detail, rather than measuring aggregate benefits and services offered by the state.

Many studies of welfare states subsequent to Esping-Andersen’s (1990) original typology discuss defamilization based on gender dynamics. Lewis (1992) categorizes welfare states based on the strength of the male breadwinner model; Orloff (1993) assesses how well women can access paid work and maintain a family; Sainsbury (1999) makes individuals the unit of analysis, rather than focusing on gender as a whole, to measure women’s contribution and provide individual earner-carer models for categorizing welfare states. Esping-Andersen (1999) has also reassessed his welfare state typology with the concept of defamilization included, and Leitner (2003) specifies four levels for defamilization. Bambra’s (2007) cluster analysis, which presents five defamilization models with gender perspectives included, is considered a methodological step forward from Esping-Andersen’s (1990) method of using averages, weighted values, and standard deviations. Cho (2014) has recently suggested a defamilization typology based on Bambra’s (2007) work, discussing women’s economic independence in welfare states by comparing gender employment and wage gaps, paternal leave, and spending on childcare and elderly care among clusters of welfare states.

Leitner’s (2003) work is distinct from other defamilization typologies in that it suggests various concepts and levels of defamilization, ranging from familialism to defamilialism, rather than simply discussing whether a state is defamilialized or not in light of gender perspectives. Leitner (2003) focuses on the caring function of the family, redefines the concept of familialism by introducing a more predictable indicator, such as policies that actively support the family in its caring function, and suggests four ideal types of familialism: optional, explicit, implicit, and defamilialism. However, although like other feminist scholars she does analyze whether the state socializes the family’s care functions by preserving them, for example by providing benefits and time for caring for children and elderly relatives, she does not examine whether the state provides such services directly or whether the family buys services in the market with various provisions from the state.

Defamilization typology based on policy tool mixes

Most previous studies adopt a two-dimensional approach to the state and family when discussing the characteristics of defamilization. In other words, regardless of whether the characteristics or implementation of social policies are defamilistic, a state’s level of defamilization is assessed by whether the family’s care responsibility is socialized based on gender relations in the labor market and family. This approach is in line with the feminist criticism of defamilization. Commodification of women’s labor is not induced by defamilization of care. Care deficits are induced as the commodification of women’s labor progresses, and defamilization is a response to this new social risk. Therefore, from a gender perspective, feminist scholars believe it should be possible to defamilialize care burdens by resolving the gender gap in the labor market (Bambra, 2006; Baxter et al., 2005; Bittman et al., 2007; Cho, 2014; Kröger, 2011; León, 2009; Michoń, 2008).

Among the various social policies that socialize family care responsibilities, childcare policies are essential to a discussion of the commodification of women’s labor force, as the modern welfare state presupposes a family composed of a heterosexual couple and their children. For women to participate in the labor market, childcare must be provided by an agent other than the children’s mother. Yoon (2014) adds the market into the binary dynamics of state and family and categorizes childcare policies based on defamilistic characteristics. This perspective is valid in that historically, defamilization of childcare has not induced labor commodification for women with children. In other words, in the commodification process for women with children, when the state does not provide sufficient childcare facilities, responsibilities are bought through the market or taken on by close relatives as a replacement for the mother.

When discussing and categorizing the defamilistic characteristics of childcare policies, the market must be considered an important pillar alongside the state and the family, and levels of childcare responsibility among the state, market, and family must be assessed (Yoon, 2012, 2014). Research on welfare state defamilization typologies has not yet focused on identifying the main agent of defamilization. Current typologies are limited in their ability to judge whether an increase in childcare policies (representative defamilization policies that offer childcare outside the family) is due to the attempt to commodify women’s labor or a market response to increased labor market participation by women, and the reason for the increase may have a considerable effect on policy outcomes. Therefore, the defamilistic characteristics of expanding childcare policies must be discussed in terms of whether the main agent of childcare is the state, market, or family.

This study attempts to categorize defamilization as either state-centric or market-centric depending on the amount of childcare responsibility borne by the state and the market. Because the family is the main agent of familialization, and thus cannot be the main agent of defamilization, levels of familialization are not discussed; this article’s focus is whether the main driver of defamilization is the state or the market.

State-centric defamilization occurs when the state bears the greatest responsibility for childcare, and is characterized by minimal market intervention and primarily state-provided childcare services provided. Methods to minimize market intervention could include providing childcare services directly, such as state-run day cares and preschools; contracting private day cares and preschools to be regulated by the state; or strongly regulating childcare service quality regardless of provider.

Market-centric defamilization occurs when families purchase required childcare services from the market. Specifically, families manage care work traditionally performed within the family by selecting and purchasing childcare services from the market sector, such as private day cares and preschools. Market-centric defamilization is characterized by low state intervention from the state and supply and purchasing of childcare services within the market system. Childcare service quality is dictated by the market rather than regulated to meet a certain standard by the state, with demand focused on day cares and preschools that offer high-quality services.

State-centric and market-centric defamilization can be distinguished by assessing state intervention based on the mix of policies implemented to realize policy goals. Kwon (2009) advances Salter’s (1998) work based on Rose’s (1993) model, focusing on delivery of social policies according to Jeon’s (2007) classification of the directness and coerciveness of government policy tools. In particular, Kwon (2009) suggests types of policy tool mixes that can be applied to assess the roles of the state and the market in a given system. Kwon’s (2009) model is distinct from Rose’s (1993) and Salter’s (1998) in that it associates provision and regulation of welfare with service creation and service quality regulation, respectively, and assesses the strength of state intervention versus market intervention according to Jeon’s (2007) concepts of directness and coerciveness. Kwon (2009) suggests that assessing directness in financing and service creation and coerciveness in service quality regulation can capture the state’s and market’s roles in implementation of social policy. Categorizing state intervention according to these criteria reveals eight policy mix models, as shown in Table 1.

Table 1.

Mixes of policy tools by types of state intervention.

Model	Financing (Directness)	Service creation (Directness)	Service quality regulation (Coerciveness)
1	State (High Directness)	State (High Directness)	State (High Coerciveness)
2	State (High Directness)	State (High Directness)	Market (quasi-government) (Medium Coerciveness)
3	State (High Directness)	Market (quasi-government) (Medium Directness)	State (High Coerciveness)
4	State (High Directness)	Market (Low Directness)	Market (Low Coerciveness)
5	Market (Medium Directness)	State (High Directness)	State (High Coerciveness)
6	Market (quasi-government) (Medium Directness)	State (High Directness)	Market (Low Coerciveness)
7	Market (quasi-government) (Medium Directness)	Market (Low Directness)	State (High Coerciveness)
8	Market (Low Directness)	Market (Low Directness)	Market (Low Coerciveness)

Source: Kwon (2009).

Parentheses indicate the directness and coerciveness of the state’s intervention. ‘Quasi-government’ refers to a state in which the market performs public functions with the government’s cooperation and control.

Model 1 features the state directly providing resources and services with strict regulations, limiting citizen choice in service providers and lacking a systematic complaint mechanism. Model 2 introduces market mechanisms to enhance service quality regulation. In Model 3, government funds private institutions, but users struggle with service costs and quality evaluation. Model 4 addresses this by offering vouchers for preferred institutions, enabling user choice and reducing state oversight. Model 5 requires citizens to pay for services in state-owned institutions, while Model 6 has them cover costs for state-created services, relying on user choice without state regulation. Model 7 involves citizens paying for private services with state oversight on appropriateness and costs, whereas Model 8 has private institutions managing all financing, provision, and regulation. Models 7 and 8 can limit access for financially strained individuals. Collectively, these eight models represent ideal types, with real-world social services often combining elements from each.

Research design

Method

The analytical method employed in this study is Fuzzy-set Ideal Type Analysis. This approach utilizes fuzzy set theory to assess how closely the subjects of analysis align with the concept of an ideal type represented as a fuzzy set, quantified by fuzzy membership scores. This method enables the transformation of existing raw data into fuzzy set membership scores, facilitating the analysis of both the degree of belonging to each type and the direction of changes over time (Kvist, 1999).

Fuzzy set theory, first introduced by Lofti Zadeh in 1965, serves as an extension of classical set theory (crisp set). In contrast to traditional sets, which permit only two membership scores – 1 (present) and 0 (absent) – fuzzy sets transcend this binary classification of ‘membership’ and ‘non-membership’, allowing for the measurement of a range of membership scores between 0 and 1 (Ragin, 2000). Consequently, Fuzzy-set Ideal Type Analysis can assess differences in both partial membership and degree, making it particularly effective for explaining hybrid cases or countries that traditional clustering methods often overlook in empirical type analysis.

The procedure for conducting Fuzzy-set Ideal Type Analysis is summarized as follows. To convert each category into fuzzy scores, it is essential to standardize each indicator initially. This standardization reduces the researcher’s subjectivity and arbitrariness. During fuzzy set analysis, a calibration process is applied to convert the variables into fuzzy scores. If this process is applied to variables that have not been standardized beforehand, it may result in arbitrary qualitative transition points for each variable (Jung and Yang, 2012). This study adopts this approach by standardizing the variables in each category using their maximum and minimum values, as demonstrated in the following equation (1), to produce values ranging from 0 to 1

Z_{v} = \frac{V - m}{M - m} = v : v a r i a b l e, M : m a x i m u m, m : m i n i m u m

(1)

Next, the standardized values of each variable will be converted into fuzzy set membership scores using the calibration function of fuzzy set analysis. While comparing standardized values prior to their conversion can help interpret the relative positions of countries or variables, it does not provide insight into the extent of those positions.

Calibration establishes three fundamental boundaries: complete membership (FI: Fully in or Fully membership), corresponding to 1 in traditional set theory; non-membership (FO: Fully out or Full non-membership), corresponding to 0; and the crossover point at 0.5, which serves as the threshold between these two categories. In this study, values corresponding to 95% were set for FI and 5% for FO, following Ragin’s (2008) recommendations, with the threshold based on the mean value. The formula for calculating fuzzy membership scores (Fuzzy Membership Score) is as follows

D e g r e e o f M e m b e r s h i p = e x p (l o g o d d s) / (1 + e x p (l o g o d d s))

(2)

In this study, fuzzy membership scores derived from this formula are interpreted as strong membership scores if they exceed the threshold (0.5) and as low membership scores if they fall below it.

In addition, fuzzy membership scores are calculated and interpreted according to three principles. The first is the principle of negation, which allows for the establishment of a negative category for each category by calculating ‘1 – the fuzzy set membership score of that category’. The second is the minimum principle, meaning that the model representing each ideal type adopts the minimum fuzzy set score among the scores of its constituent elements. The third is the maximum principle, which indicates that the type with the highest fuzzy membership score, considering the final calculated scores, represents the type of that country (Kvist, 1999).

Data and measurements

This study aimed to classify the childcare policies of OECD member states based on three causal conditions while examining how these conditions are consolidated in countries with high levels of women’s labor force participation. For data selection, the analysis focused on relatively stable or long-standing OECD member countries, excluding those with recent membership. However, countries with missing annual data or incomplete variables were excluded, regardless of these criteria, due to data inconsistencies. Table 2 outlines the key variables utilized in the analysis.

Table 2.

Composition of variables.

Cause and result condition	Variable		Definition
Cause	Directness of funding	Cost: negative value of the proportion of co-payment to net income for a dual-income family with two infant children receiving childcare in 2015 (%)	Ratio of actual childcare costs to income for dual-income families with two children, excluding government support (e.g. cash subsidies, tax benefits). Assumes both parents are full-time employees earning 100% and 67% of the average income, with children aged 2 and 3, standardized
	Directness of service creation	Service: utilization rate of national public institutions for preschool children in 2015 (%)	Proportion of applicants to public pre-primary education facilities among all service users
	Coerciveness of service quality regulations	Quality: monitoring intensity of childcare and pre-primary education services in 2013 (%)	Proportion of implemented items across six categories (inspections, surveys, and peer reviews conducted by external organizations, along with peer reviews, staff tests, and self-assessment/evaluation conducted internally)
Result	Defamilization	Employment: women’s labor force participation rate in 2015 (%)	Employment rate of women aged 15–64

Source: Extracted from OECD data (https://data.oecd.org).

The causal conditions examined in this study are derived from prior research and include the directness of financing, the directness of service creation, and the coerciveness of service quality regulations. The outcome condition is defamilization, which is measured using the women’s labor force participation rate.

The directness of funding is assessed by calculating the proportion of co-payment relative to the net income of a dual-income household, based on the provision of childcare for two infant children. A lower proportion indicates a higher degree of direct state funding. In the analysis, negative values were adjusted so that higher numerical values reflect greater directness in state funding.

The directness of service provision is measured by the utilization rate of national public childcare institutions before children enter school. A higher utilization rate suggests a greater level of direct state involvement in service provision. However, this measure must account for various institutional support mechanisms that enable parents to provide direct care for infants.

The coerciveness of service quality regulation is evaluated by monitoring the intensity of oversight in childcare and pre-primary education services. This study measured coerciveness using the proportion of implemented activities across six categories: inspections, surveys, and peer reviews conducted by external organizations, alongside peer reviews, staff evaluations, and self-assessments conducted internally. A higher proportion indicates greater coerciveness in service quality regulation.

The directness of funding and service provision was measured using 2015 data, while the coerciveness of service quality regulations was assessed with 2013 data, serving as the causal conditions. The outcome variable, women’s employment rate, was based on 2015 statistics. Since the only available data on the intensity of childcare and pre-primary education monitoring – used to measure the coerciveness of service quality regulations – was from 2013, the analysis employed the closest available data to 2013 for the other causal and outcome variables.

The OECD statistics used in this study are outdated, and a 2024 update to the OECD Stat website introduced revised definitions, complicating comparisons between 2015 and recent data. For the Cost variable, the average net childcare cost as a share of household income among OECD countries dropped from 15.5% in 2015 to 9% in 2022, with country rankings remaining stable despite differing household types in the data sets. The Service variable, focused on pre-primary education enrolment, had no data beyond 2015, precluding comparisons with the 2020s. For the Employment variable, women’s labor force participation (ages 15–64) reached a record 67.1% in Q2 2024, up from 63.5% in 2015, while men’s participation was 81% and the overall rate was 74%, with little change in country rankings.

Findings

The descriptive statistics of the variables are presented in Table 3. In the 19 OECD member countries analyzed, the state covers approximately 84.6% of the childcare costs for infants in an average household, and about 58.3% of young children utilize public childcare and early education facilities. Assuming that full government regulation of childcare services corresponds to a score of 100, the intensity of service quality regulation is interpreted to be at 51.3%. Regarding the outcome variable, the average women’s employment rate across the 19 countries is found to be 63.5%.

Table 3.

Descriptive statistics.

Condition	Variables	Mean	Standard deviation	Minimum	Maximum
Cause	Cost (C)	15.40816	9.902974	1.1605	40.772
	Service (S)	58.25665	32.22659	1.4903	96.799
	Quality (Q)	51.31579	19.16822	16.667	83.333
Result	Employment (E)	63.51504	6.794422	44.675	73.975

Table 4 displays the fuzzy scores for each country, with values ranging from 0 to 1. Following Ragin’s (2008) guidelines, full membership is assigned to values at 95% and full non-membership to those at 5%. The threshold for membership was determined based on the mean value. The fuzzy score for the Cost variable is calibrated by converting it to a negative value, as explained in the variable construction process.

Table 4.

Fuzzy score.

Country	E	C	S	Q
Australia	0.85	0.55	0.12	0.03
Belgium	0.43	0.83	0.47	0.16
Czech Republic	0.67	0.48	0.97	0.5
Germany	0.9	0.97	0.27	0.5
Finland	0.85	0.63	0.95	0.84
France	0.65	0.87	0.93	0.84
Ireland	0.5	0.29	0.04	0.03
Japan	0.77	0.72	0.17	0.16
Korea	0.31	0.95	0.12	0.84
Luxembourg	0.58	0.76	0.94	0.16
Mexico	0.03	0.49	0.93	0.84
Netherlands	0.94	0.49	0.82	0.5
New Zealand	0.9	0.2	0.03	0.5
Norway	0.96	0.93	0.57	0.5
Portugal	0.54	0.94	0.58	0.16
Slovak Republic	0.53	0.67	0.96	0.97
Slovenia	0.57	0.87	0.96	0.84
Sweden	0.97	0.95	0.92	0.97
United Kingdom	0.9	0.03	0.53	0.7

Sweden recorded the highest fuzzy score for the outcome variable Employment at 0.97, followed by Norway (0.96) and the Netherlands (0.94). In contrast, Mexico had the lowest score at 0.03, with South Korea (0.31) and Belgium (0.43) close behind. This indicates that women’s employment rates are relatively high in Sweden, Norway, and the Netherlands, but comparatively low in Mexico, South Korea, and Belgium.

Among the causal variables, Germany had the highest fuzzy score for Cost at 0.97, followed by South Korea and Sweden, both scoring 0.95. The United Kingdom recorded the lowest score at 0.03, with New Zealand (0.20) and Ireland (0.29) also ranking low. This suggests that Germany, South Korea, and Sweden provide substantial financial relief for childcare costs.

For the Service variable, the Czech Republic had the highest score at 0.97, followed by the Slovak Republic and Slovenia (0.96), and Finland (0.95). New Zealand had the lowest score at 0.03, with Australia and South Korea at 0.12, and Japan at 0.17. These results suggest that countries like New Zealand, Australia, South Korea, and Japan rely more heavily on privately operated childcare and early education services than on public ones.

In the Quality variable, Sweden and the Slovak Republic had the highest scores at 0.97, followed by Finland, France, South Korea, Mexico, and Slovenia at 0.84. Australia and Ireland had the lowest scores, both at 0.03. This indicates that Sweden, the Slovak Republic, Finland, France, South Korea, Mexico, and Slovenia enforce relatively stringent regulations on childcare service quality.

Table 5 presents a truth table derived from the fuzzy scores. In fuzzy logic, a truth table is a structured tool used to organize the outcomes of defined rules and membership functions. It tabulates the values produced by the membership function for specific input values. With three causal variables, a total of eight possible combinations could be generated; however, six set types with actual cases were identified. Considering the SYM consistency score, the combinations Csq and csq showed values above 0.9. The CSq combination had a SYM consistency score of 0.895705, which is close to 0.9.

Table 5.

Truth table.

Set type	C	S	Q	No. of cases	Raw consist.	PRI consist.	SYM consist
Csq	1	0	0	3	0.968109	0.931372	0.931373
csq	0	0	0	1	0.921384	0.814815	0.964912
CSq	1	1	0	2	0.918067	0.789189	0.895705
cSQ	0	1	1	2	0.874674	0.731844	0.731843
CSQ	1	1	1	5	0.848787	0.743961	0.870056
CsQ	1	0	1	1	0.81962	0.650307	0.716216

raw consist: the proportion of cases in each truth table row that display the outcome. PRI consist: an alternative measure of consistency (developed for fuzzy sets) based on a quasiproportional reduction in error calculation. In crisp set analyses, this will be equal to raw consist. SYM consist: an alternative measure of consistency for fuzzy sets based on a symmetrical version of PRI consistency.

Table 6 summarizes the countries analyzed within the identified combinations, presenting a childcare topology for 19 OECD countries. The analysis identified six types of childcare policy tool mixes: (1) Csq, (2) csq, (3) CSq, (4) cSQ, (5) CSQ, and (6) CsQ. These results reflect the predominant characteristics of each type across the 19 countries. However, a country’s inclusion in a specific type does not imply that it consistently exhibits those characteristics in terms of financing, service provision, or quality regulation. Since these results are based on the relative values of individual countries within the study’s data set, the characteristics of each type may not remain consistent across all countries.

Table 6.

Typology by mixes of childcare policy tools.

Set type	Set characteristics	Country
Csq	Government’s high directness of funding, low directness of service creation and low coerciveness of service quality regulations	Australia, Belgium, Japan
csq	Government’s low directness of funding, low directness of service creation and low coerciveness of service quality regulations	Ireland
CSq	Government’s high directness of funding, high directness of service creation and low coerciveness of service quality regulations	Luxembourg, Portugal
cSQ	Government’s low directness of funding, high directness of service creation and high coerciveness of service quality regulations	Mexico, United Kingdom
CSQ	Government’s high directness of funding, high directness of service creation and high coerciveness of service quality regulations	Finland, France, Slovak Republic, Slovenia, Sweden
CsQ	Government’s high directness of funding, low directness of service creation and high coerciveness of service quality regulations	Korea

Csq refers to cases where the government provides childcare services with high directness of funding but low directness of service creation and low coerciveness of service quality regulations. In this model, the focus is on reducing childcare costs for households, with services predominantly provided by the market rather than the state, and lenient quality regulations. Examples include Australia (E: 0.85), Belgium (E: 0.43), and Japan (E: 0.77). csq reflects a scenario where the government exhibits low levels of funding, service creation, and quality regulation. Here, the market plays the central role in delivering childcare services. Ireland (E: 0.5) fits into this type. CSq indicates that the government actively reduces childcare costs while ensuring high participation in public childcare and early education services. This type includes Luxembourg (E: 0.58) and Portugal (E: 0.54). cSQ represents a model focused on providing childcare through public facilities, with strong quality regulation, rather than directly reducing childcare costs. Examples include Mexico (E: 0.03) and the United Kingdom (E: 0.9). CSQ corresponds to cases where the government demonstrates high levels of funding, service creation, and quality regulation. Countries in this type include Finland (E: 0.85), France (E: 0.65), the Slovak Republic (E: 0.53), Slovenia (E: 0.57), and Sweden (E: 0.97). CsQ describes a policy approach where the government focuses on reducing childcare costs for households while strongly regulating the quality of market-based childcare services. South Korea (E: 0.31) belongs to this category.¹

According to the truth table analysis in Table 7, ~S*~Q meets the consistency threshold of 0.8 or higher. This result suggests that women’s employment rates tend to be higher when the directness of government service creation and coerciveness of service quality regulations are low. In other words, employment rates are often higher when childcare services are predominantly market-driven rather than directly provided or heavily regulated by the government. The solution coverage was approximately 88.8%, with a solution consistency of 74.0%. In summary, while the solution consistency falls short of 0.8, the results indicate that women’s employment rates are higher when childcare services are predominantly market-driven.

Table 7.

Truth table analysis.

Set type	Raw coverage	Unique coverage	Consistency	Solution coverage	Solution consistency
C	0.763424	0.120623	0.777338	0.887938	0.740428
~S*~Q	0.418677	0.0669261	0.886326
S*Q	0.520623	0.0365759	0.797378

The analysis highlights that traditional welfare states like Finland, France, and Sweden effectively balance affordability and quality by reducing childcare costs and maintaining high-quality public services. In contrast, the United Kingdom, as a liberal welfare state, focuses on service quality and regulation over cost reduction. Employment rates, particularly for women, are higher in countries with market-driven childcare systems, suggesting that childcare defamilization has been largely market-driven rather than government-led. While policy initiatives may have supported childcare expansion in some cases, traditional welfare states stand out for addressing care deficits through robust public provisions.

Defamilization typologies, rooted in feminist critiques of welfare state models, incorporate gender dimensions into comparative welfare state analyses. While most studies emphasize the need for defamilization in welfare discussions or examine country-specific characteristics within existing typologies (Daly, 1994; Lewis, 1992; Lister, 1994; Orloff, 1993; Sainsbury, 1994), Cho (2014) proposed a typology using variables like the gender employment gap, gender wage gap, father-specific leave, and spending on childcare and eldercare. Cho’s analysis identified four types, differing from traditional typologies, with Denmark, Norway, and Sweden grouped together, but Finland, the United Kingdom, Australia, and France classified under the same type. This study categorizes welfare states based on whether the state or market is the primary agent of childcare defamilization, identifying six distinct types independent of existing classifications. However, differences in analyzed countries, variables, and typology focus should be considered when interpreting the findings.

Conclusion

This study utilizes fuzzy set analysis to categorize childcare policies, considered typical defamilization policies, across 19 OECD member countries. To discern whether defamilization is state-centered or market-centered, the study employs policy tool theories that explore the mixes of policy tools based on different types of state intervention. Specifically, it examines whether the agents of defamilization are the state or the market by analyzing the directness of funding, service creation, and the coerciveness of service quality regulations.

To facilitate this analysis, the following cause variables were established: the proportion of co-payment to net income for a dual-income family with two infant children receiving childcare (directness of funding), the utilization rate of national public institutions for preschool children (directness of service creation), and the monitoring intensity of childcare and pre-primary education services (coerciveness of service quality regulations). The outcome variable assessed was the women’s employment rate, and fuzzy set methodology was applied for categorization.

The analysis classifies childcare service models into six types based on government involvement and market dynamics:

Csq: Characterized by high directness of funding, low directness of service creation, and lenient quality regulations, where the market predominantly provides services. Examples include Australia, Belgium, and Japan.

csq: Defined by low levels of government funding, service creation, and regulation, with the market playing a central role in childcare delivery. Ireland exemplifies this type.

CSq: Reflects active government efforts to reduce childcare costs while ensuring high participation in public services. This model is represented by Luxembourg and Portugal.

cSQ: Focuses on providing childcare through public facilities with strong quality regulation, rather than directly reducing costs. Examples include Mexico and the United Kingdom.

CSQ: Features high levels of government funding, service creation, and regulation, exemplified by Finland, France, the Slovak Republic, Slovenia, and Sweden.

CsQ: Describes a policy approach where the government aims to reduce childcare costs while rigorously regulating the quality of market-based services. South Korea falls into this category.

Interestingly, both the United Kingdom, which has a relatively high women’s employment rate, and Mexico, which has the lowest, are classified under the same type, cSQ. Traditional welfare states such as Finland, France, and Sweden fall under CSQ, indicating that these countries effectively reduce childcare costs while maintaining public service quality. In contrast, the United Kingdom, a liberal welfare state, emphasizes providing high-quality childcare services and regulating service quality rather than expanding policies to lower childcare costs.

According to the truth table analysis, ~S*~Q meets the consistency threshold of 0.8 or higher, suggesting that women’s employment rates are generally higher when the directness of government service creation and the coerciveness of service quality regulations are low. In other words, employment rates tend to be greater when childcare services are primarily market-driven rather than directly provided or heavily regulated by the government. Although the solution consistency does not reach 0.8, the findings still indicate that women’s employment rates improve when childcare services are predominantly market-driven.

These results can be interpreted as indicating that the defamilization of childcare has primarily been driven by market forces rather than government intervention. Specifically, as women’s participation in the labor market has increased, the resulting care deficit has largely been addressed through market-driven childcare services, rather than proactive government measures. Consequently, in countries where women’s employment rates have significantly risen, there may have been an expansion of childcare services facilitated by policy initiatives. Nevertheless, the typology shows that in traditional welfare states like Finland, France, and Sweden, the government not only alleviates the financial burden of childcare but also ensures the provision of high-quality services through public facilities. This suggests that efforts to address gaps in state-centered policies have occurred simultaneously. In summary, it appears that after a substantial level of market-driven defamilization of childcare services, the state has begun to respond with policy measures as women’s labor market participation has expanded.

The limitations of this study should also be acknowledged. First, microscale variables, which may provide significant insights into a nation’s population were not directly considered in the fuzzy-set analysis. Second, only a limited number of factors derived from existing theories were included in the analysis. This limitation relates to the advantages of fuzzy set analysis, which allows for the confirmation of causal relationships regardless of changes in results caused by other variables. This methodology is particularly effective for focusing on theoretical variables and their combinations. However, it is important not to overlook other influential factors that may impact the relationship between childcare policy and women’s employment. Third, the study relies on statistics from 2013 or 2015, which may not reflect current dynamics. Limited recent data on childcare and pre-primary education monitoring required using 2013 figures and the nearest available data for other variables. Updated data is needed to validate the findings. However, a 2024 OECD Stat update revised definitions, complicating comparisons between 2015 and recent data for Cost, Service, and Employment variables. Future research should include country-specific case studies or reanalysis with comparable national-level statistics.

Footnotes

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Chae-Jeong Lee

Notes

Author biography

Chae-Jeong Lee is an Associate Research Fellow at the National Assembly Futures Institute in the Republic of Korea. Her research focuses on social policy, welfare finance, policy theory, policy analysis, and policy evaluation.

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